1. Field.
This invention relates to the field of information technology, and more particularly to the field of data integration systems.
2. Description of the Related Art
The advent of computer applications made many business processes much faster and more efficient; however, the proliferation of different computer applications that use different data structures, communication protocols, languages and platforms has led to great complexity in the information technology infrastructure of the typical business enterprise. Different business processes within the typical enterprise may use completely different computer applications, each computer application being developed and optimized for the particular business process, rather than for the enterprise as a whole. For example, a business may have a particular computer application for tracking accounts payable and a completely different one for keeping track of customer contacts. In fact, even the same business process may use more than one computer application, such as when an enterprise keeps a centralized customer contact database, but employees keep their own contact information, such as in a personal information manager.
While specialized computer applications offer the advantages of custom-tailored solutions, the proliferation leads to inefficiencies, such as repetitive entry and handling of the same data many times throughout the enterprise, or the failure of the enterprise to capitalize on data that is associated with one process when the enterprise executes another process that could benefit from that data. For example, if the accounts payable process is separated from the supply chain and ordering process, the enterprise may accept and fill orders from a customer whose credit history would have caused the enterprise to decline the order. Many other examples can be provided where an enterprise would benefit from consistent access to all of its data across varied computer applications.
A number of companies have recognized and addressed the need for sharing of data across different applications in the business enterprise. Thus, enterprise application integration, or EAI, has emerged as a message-based strategy for addressing data from disparate sources. As computer applications increase in complexity and number, EAI efforts encounter many challenges, ranging from the need to handle different protocols, the need to address ever-increasing volumes of data and numbers of transactions, and an ever-increasing appetite for faster integration of data. Various approaches to EAI have been taken, including least-common-denominator approaches, atomic approaches, and bridge-type approaches. However, EAI is based upon communication between individual applications. As a significant disadvantage, the complexity of these EAI solutions grows geometrically in response to linear additions of platforms and applications.
While existing data integration systems provide useful tools for addressing the needs of an enterprise, such systems are typically deployed as custom solutions. They have a lengthy development cycle, and may require sophisticated technical training to accommodate changes in business structure and information requirements. There remains a need for data integration methods and systems that permit use, reuse, and modification of functionality in a changing business environment. To facilitate such methods and systems, a need also exists for improved methods and systems for deploying data integration functions.